A long standing problem in radio communications is accurately determining the location of a mobile radio transmitter. Precise location information in a cellular telephone network is desirable for various reasons that have been recognized in the prior art. For example, U.S. Pat. No. 5,515,378 to Roy, III et al. discloses the application of location information to mitigating the hand-off problem, increasing signal sensitivity, reducing crosstalk, and increasing cell capacity. Also disclosed is the use of location information to dynamically track the trajectories of mobiles. This source tracking makes use of an extended Kalman filter, and can include the tracking of velocities and accelerations as well as positions, and the tracking of multiple mobiles whose trajectories cross. U.S. Pat. No. 5,512,908 to Herrick mentions the application of cellular location information to 911 dispatching, tracking unauthorized cell phone usage, and tracking or locating commercial and/or government vehicles. U.S. Pat. No. 5,327,144 to Stilp et al. also mentions various applications of mobile location information, such as locating lost or stolen vehicles, assisting lost motorists, and dispatching emergency vehicles. These applications have yet to be realized, however, because they require accurate location information and no adequate method of providing such information has yet been developed.
Multipath is the greatest obstacle to prior art methods of solving the location finding problem. As shown in FIG. 1, multipath is typically caused by the reflection of signals from objects in the environment, such as buildings, hills, and other structures. A signal transmitted from a cellular phone 30, for example, is reflected from structures 32, 34, and 36, resulting in three multipath signals arriving at a base station 38 in addition to a direct path signal. Due to the multipath signals, it appears from the perspective of base station 38 that three additional cellular phones 40, 42, and 44 are transmitting similar signals from different locations. In some cases, signals from a phone 50 can arrive at base station 38 from nearly opposite directions, one from actual phone 50 and another from a "ghost" phone 52. Moreover, because the path lengths of the multipath signals differ from that of the direct path signal, the multipath signals have differential time delays with respect to the direct path signal. In an urban environment where severe multipath is present, sometimes no direct path exists and the base station receives only multipath signals. For example, phone 46 has no direct path signal to base 38. Consequently, it appears from base 38 that a unique signal is originating from a "ghost" phone 48 which has a very different location from actual phone 46. Clearly, multipath significantly complicates the communication of signals, and, in particular, complicates the problem of accurately determining the true location of a transmitter. Since a large proportion of cellular phone usage is in urban environments which have severe multipath, it is especially important to solve this problem. All prior art methods, however, have failed to provide consistent and accurate location information in multipath environments.
As illustrated in FIG. 2, a common prior art approach to determining the position of a mobile phone 52 involves measuring temporal information, e.g. time of arrival (TOA) or time difference of arrival (TDOA), at three or more synchronized base stations 56, 58, and 60. By communicating this temporal information between the base stations over a communication line 62, the transmitter location can be determined. This type of approach is disclosed, for example, in U.S. Pat. No. 5,548,583 to Bustamante, U.S. Pat. No. 5,512,908 to Herrick, U.S. Pat. No. 5,327,144 to Stilp et al., U.S. Pat. No. 5,317,323 to Kennedy et al., and U.S. Pat. No. 4,799,062 to Sanderford, Jr. et al. These methods have the disadvantage that they require several base stations, and that signals from cellular phone 54 be received by all base stations 56, 58, and 60 simultaneously. Additionally, expensive high accuracy clocks are required at the base stations and expensive high bandwidth communication lines 62 are required between the base stations in order to allow accurate temporal correlation of their received signals from phone 54. More significantly, this approach encounters serious difficulties in urban environments since multipath causes temporal delays and creates "ghost" transmitters. Consequently, it fails to determine positions accurately and consistently in many cases.
Although the prior art does disclose several techniques for location finding that attempt to mitigate multipath effects, they all fail in the presence of severe multipath. Bustamante does not acknowledge problems due to severe multipath. Herrick teaches a method for mitigating inaccuracies due to multipath by averaging over several TOA measurements at differing frequencies. Stilp teaches a method of compensating for multipath through the use of algorithms that can distinguish direct path from multipath signals and eliminate or ignore the latter. Kennedy also teaches the mitigation of multipath through algorithms that distinguish multipath signals from direct signals by determining angles of arrival, times of arrival, and signal strength. Sanderford teaches a method for multipath mitigation using spread-spectrum (frequency hopping) transmissions from the mobiles. These techniques are all characterized by an attempt to cope with multipath by circumvention or discrimination of multipath signals from direct path signals. In cases of severe multipath, however, there often is no direct path signal at all. In such cases, these approaches fail. Moreover, averaging techniques are based on assumptions about the distribution of multipath that are not generally valid, especially in severe multipath environments. Even in cases where such assumptions do hold, these averaging techniques do not yield accurate position information.
Stilp discloses a method for location finding which involves creating a grid of theoretical signal delay values. The calculation of the theoretical values incorporates biases at the base station sites due to mechanical, electrical, or environmental factors. The biases for the base station sites are determined by measuring the signals from reference transmitters having known locations. Any variance between the known position and the calculated position is assumed to be caused by site biases. It is further assumed that these same biases will affect other cellular phones at other unknown locations, i.e. the site biases are assumed to depend only on the site and not on the mobile locations. Dues to these assumptions, the method can not account for biases due to severe multipath, which changes dramatically in dependence upon the mobile location. Moreover, since this technique is based upon TDOA measurements, it is problematic for the additional reasons already discussed.
As illustrated in FIG. 3, another prior art approach determining the location of a phone 68 makes use of antenna arrays 64 and 66 for direction finding. For example, U.S. Pat. No. 5,515,378 to Roy, III et al. discloses a method and apparatus for estimating positions and velocities of mobiles from antenna array measurements of their signals. As is well-known in the art, a processor forms an average covariance matrix from a collection of array vectors received at each antenna array and performs spatial smoothing and/or forward/backward temporal averaging as appropriate. Signal and noise subspaces are then calculated using an eigendecomposition of the resulting covariance matrix. Signal detection is then accomplished by a statistical technique such as weighted subspace fitting (WSF) detection. A maximum likelihood estimator is employed to then obtain the signal parameter estimates, such as the direction of arrival (DOA). When an estimate of location is made based only on the directional information from a single base station, such an estimate has a very poor accuracy. To obtain more accurate location estimation, the DOA parameters must be supplemented by TOA measurements and/or parameter measurements sent over a communication line 72 from other base stations. Even in this case, however, the estimates are still not sufficient to accurately determine a correct location since a direct path may not exist at all, as in severe multipath environments. For example, since no direct path exists from phone 68 to either base station 64 or 66, phone 68 will appear to be located at the location of a false "ghost" phone 70.
Other more recent work in mobile communications has attempted to cope with severe multipath, albeit not for location determination applications. For example, Gerlach et al. in "Adaptive Transmitting Antenna Methods for Multipath Environments" discloses a base station beamforming method which uses feedback from a mobile to determine a characteristic subspace of the mobile's instantaneous channel vector. Although the instantaneous channel vector can change rapidly in a strong multipath environment, Gerlach et al. point out that it is normally restricted to a characteristic subspace that is much more stable in time. By tracking this channel subspace rather than the channel vector, much lower feedback rates are required. A collection of instantaneous channel vectors are measured, and the sum of their outer products is taken to produce a channel matrix. The eigenvectors having large eigenvalues define a subspace of this matrix which is a more stable representation of the receiver's channel. This subspace is then used in beamforming at the base station to minimize crosstalk and maximize the desired signal at the mobiles. Although this approach reduces the amount of feedback required for beamforming in severe multipath environments, it does not have obvious application to location finding.
U.S. Pat. No. 4,799,062 to Sanderford, Jr. et al. proposes an approach to location finding using a differential multipath signal technique. They point out that when the positions of two mobiles are close to each other, their multipath signals should be nearly the same. Consequently, if a reference signal from a known transmitter location near the mobile were subtracted from the mobile's signal, the multipath effects should cancel and the differential position between the two could be determined. The disclosure, however, does not explain in detail how such a method might be implemented. Moreover, in severe multipath environments the approach outlined fails. Since the multipath components of the signal can change significantly over distances on the order of 10 meters or less, the differential position will be accurate only in cases where the mobile is already within sight of the mobile, therefore defeating the purpose of the technique. Even in cases of less severe multipath, the need for a reference signal makes the technique unattractive to implement.